Customer Success Performance Insight Analyst

Responsibilities

Data Architecture & Systems

• Design and build scalable reporting frameworks and data pipelines for self-service insights across customer success operations and cross-functional teams.
• Own data strategy and architecture for customer experience operations, including metric definitions, data models, and governance standards.
• Architect dashboards and data exports covering customer health, agent performance, and operational efficiency across multiple systems.
• Distinguish process issues from structural problems and determine when to optimize workflows versus redesign systems.

Analytics & Insights

• Analyze complex datasets to identify behavioral patterns, performance drivers, root causes, and operational improvement opportunities.
• Use conversation analytics, transactional data, and customer interaction data to report on revenue-impacting and experience-driving topics.
• Conduct deep-dive analyses of performance, customer satisfaction trends, and operational health metrics; translate findings into recommendations.
• Define, instrument, and track KPIs for customer experience, agent performance, operational efficiency, and AI accuracy.
• Partner with leadership through data-driven storytelling and evidence-based insights.

AI, Automation & Operations

• Design, train, and implement LLM prompts for QA automation, insight generation, and customer feedback synthesis.
• Evaluate AI-generated outputs for accuracy, clarity, and business impact; build feedback loops to improve AI systems.
• Identify and implement automation opportunities in QA, reporting, and customer feedback analysis.
• Maintain and optimize analytics platforms, dashboards, metrics, reporting pipelines, and data exports.
• Liaise with analytics platform providers to troubleshoot issues and maintain system reliability.
• Establish data quality, documentation, governance, and access standards across CX systems and reporting layers.
• Build knowledge systems, dashboards, runbooks, and documentation for human and AI consumption.
• Manage NPS outreach, including direct customer follow-up, and present targeted analyses to leadership.

Collaboration

• Collaborate with Research and Voice of Customer teams to synthesize insights and identify customer experience improvements.
• Partner with Support, Enablement, Revenue Operations, Engineering, and Data & Analytics teams on tooling, data definitions, and infrastructure.
• Deliver recurring reporting and insights to leadership through dashboards, newsletters, and executive summaries.
• Translate customer success operations needs into data requirements.

Requirements

• Advanced SQL proficiency, including complex and performant SQL for data exploration, validation, modeling, dashboards, and reporting.
• 3–5+ years of experience in data analytics, customer analytics, CX operations, quality assurance, or related roles focused on building scalable data systems and frameworks.
• Experience applying systems thinking to operations and designing scalable processes, data flows, or analytics infrastructure.
• Advanced experience designing and maintaining dashboards, reports, and data pipelines.
• Strong data fluency, including metric definition, data quality, documentation, and analytical validation.
• Experience analyzing large datasets and translating findings into actionable business recommendations.
• Experience with BI and analytics tools such as Tableau, Looker, or Sigma.
• Experience working with structured and unstructured data.
• Experience designing, training, or managing LLMs or similar AI models for evaluating customer interactions, transcripts, or agent outputs.
• Proficiency with QA platforms; Rippit or MaestroQA preferred.
• Strong troubleshooting, process optimization, communication, organization, and cross-functional influence skills.
• Ability to manage complex analytical workflows independently and collaboratively.
• High attention to detail and strong systems thinking.

Nice-to-Haves

• Experience building or maintaining customer experience, support operations, or quality assurance analytics systems.
• Experience with conversation analytics, NPS programs, or Voice of Customer initiatives.